Clifford support vector machines for classification

被引：0

作者：

Bayro-Corrochano, E ^{[1
]}

Arana-Daniel, N ^{[1
]}

Vallejo-Gutiérres, JR ^{[1
]}

机构：

[1] CINVESTAV, Ctr Invest & Estud Avanzados, Unidad Guadalajara, Comp Sci Dept,GEOVIS Lab, Guadalajara 44550, Jalisco, Mexico

来源：

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2004 | 2004年 / 3070卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces the Clifford Support Vector Machines as a generalization of the real- and complex- valued Support Vector Machines. The major advantage of this approach is that one requires only one CSVM which can admit multiple multivector inputs and it can carry multi-class classification. In contrast one would need many real valued SVMs for a multi-class problem which is time consuming.

引用

页码：9 / 16

页数：8

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